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地质灾害专业监测预警技术方法探讨 被引量:8

Discussion on Technical Method of Professional Monitoring and Early Warning for Geological Disaster
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摘要 地质灾害专业监测是明确地质灾害隐患点发展趋势的重要手段,对于危害性较大、变形发展趋势不明的地质灾害可通过专业监测预警方法进行防灾减灾。以近年来成功预警地质灾害的案例进行分析,提出地质灾害的专业监测预警工作需要满足三方面的要求才能有效发挥其作用,即智能化的监测设备有效获取关键监测数据,科学的监测方案确保监测设备布设位置可靠和恰当,过程化的预警模型准确判断地质灾害隐患点的发展趋势并提前做出预警。同时探讨了监测设备、监测方案、预警模型三方面工作的应用现状和未来发展方向,为地质灾害的专业监测预警工作提出了相应的建议。 The Professional monitoring of geological hazards is an important means to clarify the development trend of potential geological hazards. For geological hazards with greater hazards and unknown deformation development trend, the professional monitoring and early warning methods can be used for disaster prevention and mitigation. Based on the analysis of the cases of successful early warning of geological hazards in recent years, it points out that the professional monitoring and early warning work of geological hazards needs to meet three requirements in order to effectively play its role, that is, intelligent monitoring equipment can effectively acquire key monitoring data, scientific monitoring scheme can ensure that the location of monitoring equipment is reliable and appropriate, and procedural early warning model can accurately judge geological hazards. At the same time, the application status and future development direction of monitoring equipment, monitoring scheme and early warning model are discussed, and corresponding suggestions are put forward for the professional monitoring and early warning of geological hazards.
作者 亓星 QI Xing(School of Civil Engineering,Sichuan University of Science & Engineering,Zigong 643000,China;Opening Project of Sichuan Province University Key Laboratory of Bridge Non-destruction Detecting and Engineering Computing,Zigong 643000,China)
出处 《四川理工学院学报(自然科学版)》 CAS 2019年第4期49-54,共6页 Journal of Sichuan University of Science & Engineering(Natural Science Edition)
基金 国家自然科学基金(41877254) 四川省科技计划项目(2019YJ0534) 四川省重点研发项目(2017SZ0027) 桥梁无损检测与工程计算基金项目(2019QZJ02)
关键词 地质灾害 专业监测 智能设备 监测方案 预警模型 geological hazards professional monitoring intelligent equipment monitoring scheme early warning model
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